Artificial intelligence (AI) is already part of our everyday lives, whether we realize it or not. From AI‑powered search results to digital assistants that summarize emails or meetings, these technologies are increasingly enhancing how we work. Financial crime prevention is no exception.
During a recent Nasdaq Verafin webinar, we explored how AI — and more specifically agentic AI — is reshaping financial crime investigations. Throughout the discussion, it became clear that the industry is at a key moment. The scale and sophistication of financial crime continue to grow, while traditional approaches struggle to keep pace. Agentic AI represents a meaningful step forward, not by replacing expertise, but by amplifying it.
The Scale of the Challenge Demands a New Approach
According to the Nasdaq Verafin Global Financial Crime Report, an estimated $4.4 trillion in illicit funds flowed through the global financial system in 2025. That figure represents a nearly 20% compound annual growth rate since 2023. Financial institutions remain the first line of defense — but doing more of the same is no longer enough.
Most institutions are already investing heavily in people and processes. Yet nearly 60% of anti-financial crime professionals still cite inadequate resources — human and technological — as a top concern. At the same time, criminals are increasingly leveraging advanced technologies, including AI, to move faster and scale their operations. They do not face model risk committees, governance hurdles or regulatory exams. That speed advantage is real.
The good news is that regulators are recognizing this reality as well. Recent signals from FinCEN and other authorities increasingly encourage responsible innovation, including experimentation with advanced technologies. The message is clear: innovation, when done thoughtfully and transparently, is part of the solution.
AI Enhances Expertise Rather Than Replacing It
One of the most persistent misconceptions about AI in financial crime is that it’s a job stealer. In practice, what we see is the opposite. AI excels at handling repetitive, time‑consuming tasks — freeing investigators to focus on higher‑value, more complex work.
Think of AI as an accelerant for expertise. During the webinar, I shared an analogy that often resonates: a trained detection dog doesn’t replace the police officer. Rather, it helps them get to the right place faster. In the same way, AI can surface the most relevant signals, reduce false positives and provide consistent context so investigators can make better, faster decisions.
Machine learning and generative AI are already delivering tangible results across fraud and AML programs, from reducing alert volumes to improving detection rates. But agentic AI takes this one step further.
What Makes Agentic AI Different?
Agentic AI is redefining financial crime operations today. Unlike traditional systems that simply respond to prompts, agentic AI is goal‑oriented and autonomous. These systems can reason, plan and execute multi‑step tasks with minimal human input, while remaining transparent and explainable.
In practical terms, agentic AI workers can automate entire investigative workflows. They can review alerts, gather relevant data, apply consistent logic, document their reasoning and provide clear recommendations — whether that’s escalating an alert or case for further review or confidently resolving it.
This autonomy is especially powerful when paired with trusted, high‑quality data. At Nasdaq Verafin, agentic AI workers are informed by consortium intelligence from across 850 million counterparties. That means decisions are grounded in validated data, known bad actors, shared patterns and real‑world outcomes — without exposing sensitive information between institutions.
Real‑World Impact: Efficiency, Consistency and Confidence
We’re already seeing the impact of agentic AI in production environments. Our Agentic Sanctions Analyst is reducing alert workloads by more than 75% for some teams, while still delivering audit‑ready documentation for every decision. Enhanced due diligence workflows are being streamlined by automating low‑value research tasks, allowing investigators to focus on genuine risk.
Just as importantly, agentic AI drives consistency. Every alert is reviewed against the same criteria, every time. That consistency improves operational efficiency and strengthens defensibility with regulators and auditors by providing a clear, traceable rationale for each decision.
Governing AI Responsibly
Of course, adopting agentic AI isn’t a “set it and forget it” exercise. Successful institutions are investing in AI literacy, documenting risk tolerance and collaborating closely with AI governance committees. Transparency is key. Regulators will ask how AI decisions are made, what data is used and how outcomes are monitored. Institutions that can clearly answer those questions will be best positioned to move forward with confidence.
Most organizations also begin with a human‑in‑the‑loop approach — using AI recommendations while retaining final decision‑making authority. Over time, as comfort and trust increase, many find that auto‑decisioning for lower‑risk scenarios feels no different than tuning a traditional monitoring system.
Looking Ahead
AI is already transforming the financial crime landscape. Agentic AI takes that transformation further by moving us from automation to intelligence. It enables teams to work faster, more consistently and more strategically, without sacrificing transparency or control.
The institutions that succeed will be those that start now: experimenting thoughtfully, governing responsibly and partnering with providers who understand the complexity of financial crime. The challenge is enormous — but with the right tools and mindset, so is the opportunity.
To see how your peers are unlocking efficiency by putting Agentic AI into action, read our case study: FNBO Seizes the Agentic AI Advantage.
About the Author
CHUCK TAYLOR
JD, CAMS, CAFP, Head of Commercial Strategy, Nasdaq Verafin
Bringing a wealth of knowledge and experience from previous executive roles in consultancy and banking, Chuck now serves as the Head of AML Commercial Strategy for Nasdaq Verafin and is tasked with aligning sales execution with product vision and go-to-market strategies, empowering sales teams, and unlocking growth across diverse customer segments. Chuck works closely with product management teams, business leaders, and clients to ensure that the company’s offerings are aligned with current regulatory standards and effectively address the evolving challenges in the financial services industry.
In addition, Chuck serves as a subject matter expert on AML regulations, industry trends, and best practices for financial crime prevention for Nasdaq Verafin. His role involves providing strategic insights to enhance the company’s financial crime solutions and assisting clients in navigating complex compliance requirements.
